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NBA Draft 2013 started with a huge surprise at the top and remained unpredictable through the rest of it.
Because I once again gathered data for my project accuracy of NBA mock drafts I accidentally measured just how unpredictable it was! Here are some key statistics… I processed 263 NBA mock drafts and among them:Only 4 mock drafts had Anthony Bennett going number 1. F-O-U-R! That’s below 2 percent!
Congratulations to Todd Salem, Greg, Trey and Jason Quint for a really bold prediction which turned out to be accurate but, interestingly, overall their mocks were average.

66 different players appeared in at least one first round mock draft and I have to give props to Tim who was the only one with Solomon Hill included.

Around 22% of mock drafts nailed selection of Victor Oladipo at number 2 but only 6 mocks had Cody Zeller 4th to Bobcats, 21 mock drafts had Alex Len at #5, only 3 mocks had Ben McLemore at #7 and…
literally NOBODY had Nerlens Noel being drafted at #6!! How is that for unpredictable top picks?!?
For comparison, among Top7 picks in mock drafts in 2012 only Dion Waiters and Harrison Barnes were surprises on a similar scale.

On the other side, Otto Porter was at #3 in majority of mocks – 73% to be precise.

With all that said you can see why it wasn’t a great year for mock drafts’ accuracy but despite such wild Top7 and lower average score than in previous years, people at the top still managed to distance themselves from others. So…Who Had The Best and Worst 2013 Mock Drafts on the Internet?

To answer this question here’s what I did:

1) after the draft lottery I saved on my hard drive pages from as many first round mock drafts as I could quickly gather. Mostly from widely known authors/sources but I also added many googled ones and tried to include authors from last years’ post [hence the growth]. I repeated this exercise weekly up to the day before actual NBA Draft when I had a final push for the data.
In 2011 I checked 33 mock drafts, in 2012 I expanded efforts to 122, this year I ended up with 263 NBA Mock Drafts. So my quest to cover every mock available on the web continues ;-)

2) I graded every mock by an average absolute difference between the mocked and actual picks.
So for example, if you had Nerlens Noel at number 1 in your mock draft your score for #6 [where he went] was “5” but if you had him at #9 you would get a score of “3”. Simple, right?
I did the aforementioned thing for every pick in every mock and calculate an average for the entire first round so the lower the number the more accurate mock was. Players who were predicted as first rounders but were drafted in the second round counted but if a player went undrafted his position was “61”.

There are three important notes about this excercise:
– because I tried to capture content which was quickly changing some of the links provided won’t work. It’s not my fault that people use the same address or page for often changing content. I could just upload those saved files but that probably wouldn’t be legal so I just posted a PDF file with every pick of every mock I’ve processed.

– as in previous years, I didn’t try to include versions of mocks published in the last hours before the draft because not only I don’t want to chase last minute updates or rumors from teams or possible leaks but I also question the value of such mocks which are online for 50 minutes… especially when at this point you can just wait for the real event.

– it’s kind of obvious but, as a remainder, please don’t assume that mock drafts represent entire value of those sites or authors. Even if someone had a really good/bad mock it doesn’t mean their analysis of players was good/bad too. It may have been, I don’t know, I didn’t include it in any way.

NBA Draft 2012 is in the books so it’s time for a lot of grading… no, I don’t mean judging teams or drafted players because it’s too early but there’s one draft-related topic which doesn’t require waiting few years:Who Had The Best and Worst 2012 Mock Drafts on the Internet?

After humble beginnings last season I expanded my efforts to 122 NBA Mock Drafts this year.
Obviously, it doesn’t mean I covered every mock available on the web but I think I was close ;-)

Seriously speaking though here’s what I did:
1) after the draft lottery I saved on my hard drive pages from as many 1st round mocks as I could quickly gather. Mostly from widely known authors/sources but I also added many googled ones.
I repeated this exercise weekly up to the day before actual NBA Draft when I had a final push for the data.

There are two important notes here:
a) because I tried to capture content which was quickly changing some of the links provided won’t work. The most extreme example was probably with Chad Ford from ESPN who published 10 mock drafts and the last 3 or 4 had multiple “updates” which by the way block the entry to original versions.
I could just upload those saved files but that probably wouldn’t be legal so I just posted a PDF file with every pick of every mock I’ve processed.
b) I included 3 mocks from the day of the draft from [my guess at] 3 most popular sources but I don’t feel great about it. On a draft day rumors from teams, possible leaks and updates are so rampant that I question the value of those mocks for 10 minutes… especially when at this point you can just wait for the real event.

2) I graded every mock by an average absolute difference between the mocked and actual picks
For example Bradley Beal was drafted third so if you had him at #2 you would get a score of “1” but if you had him at #5 you would get a score of “2”. Got it? If a player went undrafted I counted that as a “30” because of the entire second round. I did the aforementioned thing for every pick in every mock and calculate an average for the entire first round so the lower the number the more accurate mock was.

I started this project as usual with ESPN’s play-by-play data… but after I’ve finished and compared to aforementioned sources I discovered a shocking fact: ESPN’s version has a nasty habit of changing dunks into 1-foot shots! And it’s not a small issue either – we are talking about difference of around 3000 plays per year! So those files landed in trash along mine time spent on it and I had to start from scratch.

For my second attempt I used play-by-play data from basketballvalue.com… and even though their numbers looked fine it wasn’t a smooth ride either because of another nasty habit – they identify players only by surnames… but in some games they added a first letter to make a distinction between players on different teams. Such situation creates a litany of possible identification conflicts, for example just note how many players in the NBA are named Williams or Johnson, but through battery of tests and corrections by hand I think I sorted it all out successfully.
With that said keep in mind that there could be a couple of mistakes here, especially with players who played little or those who had the same name on the same team, but overall I think it should be accurate.

I started this project as usual with ESPN’s play-by-play data… but after I’ve finished and compared to aforementioned sources I discovered a shocking fact: ESPN’s version has a nasty habit of changing dunks into 1-foot shots! And it’s not a small issue either – we are talking about difference of around 3000 plays per year! So those files landed in trash along mine time spent on it and I had to start from scratch.

For my second attempt I used play-by-play data from basketballvalue.com… and even though their numbers looked fine it wasn’t a smooth ride either because of another nasty habit – they identify players only by surnames… but in some games they added a first letter to make a distinction between players on different teams. Such situation creates a litany of possible identification conflicts, for example just note how many players in the NBA are named Williams or Johnson, but through battery of tests and corrections by hand I think I sorted it all out successfully.
With that said keep in mind that there could be a couple of mistakes here, especially with players who played little or those who had the same name on the same team, but overall I think it should be accurate.

NBA Draft 2011 didn’t disappoint in terms of providing entertainment with interesting decisions, picks and trades but it’s over so it’s time for some conclusions… no, I don’t mean judging teams or drafted players with special grading scales [where almost all teams were above average!] but to answer a question which doesn’t require waiting few years: Who Had The Best and Worst 2011 Mock Drafts on the Internet?
(You can also check expanded version for mock drafts in 2012 and 2013!)

Obviously, I couldn’t cover every mock available on the web but here’s what I did:
1) 12 hours before NBA Draft I saved on my hard drive pages from as many latest 1st round mocks as possible. Mostly from widely known authors/sources but I also added some random googled ones.
For more fun and information I also added older versions.
2) I graded every mock by an average absolute difference between the mocked and actual picks.
For example Derrick Williams was drafted at #2 so if you had him at #1 you would get a score of “1” but if you had him at #5 you would get a score of “3”. Got it? If a player went undrafted I counted that as a “30” because of the entire second round. I did the aforementioned thing for every pick in every mock and calculate an average for the entire first round so the lower the number the more accurate mock was.

BTW, if you are interested what’s the score for YOUR mock draft let me know in the comments.
Although there better be some kind of valid information about a date.
It won’t be fun to judge mock which has been written after real draft ;-)

In part 1 I focused on a difference between players who were drafted at any given spot and those who would have been drafted there had lottery played out exactly as odds suggested. In part 2 I’ll take into consideration those odds. Incidentally I’ve stumbled into a solid way of quantifying how well teams have drafted!

But first, here’s a remainder of rules which were used:
– I assumed continuity of teams so “OKC Thunder” means “Seattle SuperSonics” in earlier years,
– I included new ownership of picks via trades only when they were completed before making a pick,
– I assumed that Career Win Shares in regular season adequately describe player’s career,
– I assumed that players would be drafted at the same slot no matter which team have owned given pick.

What’s more, I changed perspective to the Last 10 Years because IMHO drafts from 1995 to 2000 had too big impact on numbers because careers of those players have lasted way longer than any other. For every season in last decade I re-created probabilities of getting every pick before draft [this is an example from 2010]:Read the rest of this entry »